The brain is an interconnected network of specialized, electrically active cells called neurons. A new area of neuroscience, called connectomics, aims to describe the complete set of connections between cells within and between brain areas. This is important as it allows neuroscientists to decipher the ‘circuit logic’ of how information is processed by the brain and linked to behaviors. This is critically relevant to the research and therapeutic strategies in the treatment of human brain disorders and mental health, as disruptions in information processing often affects learning, memory and thought processes. These disruptions can occur at the junctions where neurons connect, called synapses.

Spotting the ConnectionNeuronal connections are so tiny (measured in nanometres) that it is hard to see them with a light microscope. Instead, powerful electron microscopes are used to take high resolution snapshots through the tissue, detailing structures less than 1/10,000th of a hair’s width, and revealing the many thousands of synapses that form the basis of circuit connections.
The next step is to recreate a 3D image from the 2D images taken by the electron microscope and build a picture of how neurons in a ‘connectome’ are linked, to better understand the circuit and how the information it carries is processed by these neurons. However, reconstructing circuit maps on such a scale is a challenge.

Many synaptic connections need to be manually identified from large image datasets, 10-1000s of terabytes (TB’s) in size; where each TB is 1000 gigabytes (GB’s). Powerful computing resources and many man-hours are needed to do this, making experimental approaches to test circuit hypotheses at this level unfeasible.
New ApproachOur new study aims to bring together several technological approaches that will aid the connectomics effort and streamline the imaging of synaptic units in brain circuits. In our approach, we combined cell labeling, multimodal-imaging and computational techniques to zoom in on neuronal circuitry. The techniques were developed at the MRC’s Laboratory of Molecular Biology, Cambridge, UK, and the University of Cambridge’s Department of Zoology, Cambridge, UK, in collaboration with specialists for X-ray and correlative 3D microscopy at ZEISS.

We engineered the fruit-fly (Drosophila melanogaster) to produce an electron dense dye in neurons of interest in its brain. We were then able to detect these neurons of interest and their synapses in the fruit-fly brain using non-destructive, high-resolution X-ray imaging (micro-tomography). Using this information, we zoomed in on these neurons under the electron microscope (EM) to investigate the synapses in greater detail. This work-flow afforded more focused targeting of brain regions, enabling us to pinpoint regions of interest, like the learning and memory centers. We also describe computational methods that can be used in a rapid, automated way to identify neurons we were specifically interested in and even smaller structures, such as mitochondria, important for energy production in cells.

Mapping Memories
Storing and retrieving memories is vital to the brain’s control of behavior, and there is deep conservation in how these brain areas work across the animal kingdom. Because of this, investigating functional changes in brain connectivity in fruit-flies is relevant to our understanding of human brain connectomics.

It is generally thought that long-term memories (lasting days or more) are stored by changing the strength of connections between neurons. Despite intense study, proving exactly what changes happen in neurons to store memories remains a key open problem, but one that we can systematically address in the fruit-fly brain. In future studies using our combined imaging and computational approaches, we will focus on known brain circuits and compare whether the storage of different kinds of memory produces different structural changes in the brain. While our technical studies focus on flies, these approaches are also applicable to other animal studies, such as mice, and similar technical approaches are being explored in the US.

Together, we hope these studies can help neuroscientists and clinicians understand how memory loss can be prevented as well as curb the recall of traumatic events.